用神经网络方法在线求解经济调度问题并与经典方法比较

A. Mohammadi, M. Varahram, I. Kheirizad
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引用次数: 28

摘要

本研究比较了求解经济调度问题的两种方法,即Hopfield神经网络和lambda迭代法。考虑了3台、6台和20台电力系统的三个样本。计算了解决这两个系统的经济调度所需的CPU时间。研究表明,对于在线经济调度,Hopfield神经网络比经典方法更有效,收敛时间也更短
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Online Solving Of Economic Dispatch Problem Using Neural Network Approach And Comparing It With Classical Method
In this study, two methods for solving economic dispatch problems, namely Hopfield neural network and lambda iteration method are compared. Three sample of power system with 3, 6 and 20 units have been considered. The time required for CPU, for solving economic dispatch of these two systems has been calculated. It has been shown that for on-line economic dispatch, Hopfield neural network is more efficient and the time required for convergence is considerably smaller compared to classical methods
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